Cross-Layer Adaptive Feedback Scheduling of Wireless Control System

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Cross-Layer Adaptive Feedback Scheduling of
Wireless Control System

• Presented by Bin Tang

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Wireless Control Systems (WCSs)

• Spatially distributed nodes of sensors,
  controllers, and/or actuators interconnected with
  wireless links
• Advantages
• Flexible installation and maintenance, mobile
  operation
• Hazardous and inaccessible environment
• Cheaper cost
• Disadvantages
• Path loss, multi-path fading, interference, etc
• Delay, packet losses, jitters get more pronounced

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WCS System Model

• Independent control loop
• Smart sensor (S)
• Smart actuator (A)
• Controller (C)
• Physical process (P)
• IEEE801.11b
• Variable channel capacity
• Control performance is decided by Deadline Miss
  Ratio (DMR)

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Deadline Miss Ratio (DMR)

• Deadline is equal to the sampling period
• Two cases for DMR
• Sample data/control command is lost through
  wireless medium (bit error, interference, varying
  strength)
• Control command is received by actuator, later
  than deadline

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Cross-layer adaptive feedback scheduling (CLAFS)
scheme

• Information exchanging b/w application layer and
  physical layer
• Dynamically adjust sampling period w.r.t.
• transmission rate
• deadline miss ratio (DMR)
• Feedback scheduler
• uses PID algorithm with adaptive parameters
• Event-driven invocation algorithm

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Sampling Period

• Sampling period of the control loop
• QoC and workload
• Delay and DMR
• Adjust sampling period based on transmission rate
  and DMR

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Analysis of DMR over WLAN

• DMR at appropriate non-zero desired
• Smaller sample period, larger DMR
• Larger sample period, poorer Quality of Control

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PID (Proportional-Integral-Derivative) control
algorithm
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feedback scheduling

• Sampling period at jth invocation instant of the
  feedback scheduler
• h(j) minh(j-1)?h(j), hmax
• hmax maximum allowable sampling period
• ?h(j)Ke(j)
• e(j)?(j)-?r actual and setpoint DMR
• K proportional coefficient

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Proportional Coefficient K

• K0 from simulation
• ??, ??- parameter

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Optimal Quality of Control (hr, ?r)
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Event-triggered invocation

• Time-triggered not suitable for wireless
• A
• Execution-request event iff ?(j)-?rd

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Performance Evaluation

• Matlab with TrueTime toolbox
• Two scenarios
• Scenario I Controller and process close to each
  other 11Mbps no interfering
• Scenario I Increased distance 5.5 Mbps
  interfering signal

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Wireless Sensor/Actuator Network Design for
Mobile Control Applications
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Semi-Automated Architecture
Automated Architecture
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Experimental Analysis of Link Quality
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Dealing with Packet Loss on Actuator

• Idea when sensor data lost, actuator still
  produce control command
• Prediction from prev commands
• û(k) estimate of k-th control command

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• Inverted pendulum system
• PID control algorithm

r(k) desired system output y(k) measured
system output
Integral of absolute error (IAE)
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Random Thoughts

• Control Side
• How to find the optimal operating point (hr, ?r)?
• So far reactive, not proactive
• Automated or semi-automated?
• Wireless Network Side
• Can MAC layers and routing algorithms play a more
  active in WCS?
• Sensors/actuators/controllers coordination is not
  considered
• Data sensed by sensor is solely for the purpose
  of control
• Control application and other applications
  together